Data Science using R (2018)

References

• "A cartoon guide to statistics" by L Gonick and W Smith
• "R for Data Science" by G Grolemund and H Wickham
• "Advanced R" by H Wickham
• "R packages" by H Wickham
• dplyr (data wrangling)
• Chapter from "R for Data Science" (above): "Data transformation"
• Part II from "R for Data Science" (above): First chapter in Part II: "Chapter 9: Introduction"
• Tidy Animated Verbs
• ggplot2
• "ggplot2 : Elegant Graphics for Data Analysis" by H Wickham (available online via SpringerLink)
• ggplot2 online documentation
• Vignette on aesthetic specifications
• Chapter from "R for Data Science" (above): "Data visualisation"
• "An Introduction to Statistical Learning - with Applications in R" by G James, D Witten, T Hastie and R Tibshirani
• "The Elements of Statistical Learning: Data Mining, Inference, and Prediction" by T Hastie, R Tibshirani and J Friedman
• "Happy Git and GitHub for the useR" (A work in progress) by Jenny Bryan and the STAT 545 TAs
• "data organization - organizing data in spreadsheets" by Karl W. Broman (also Github for paper)

Cheat sheets

• R Reference Card
• Base R
• RStudio IDE
• R Markdown
• R Markdown Reference
• Advanced R
• Data visualisation (ggplot2) (also refer to docs.ggplot2.org/current)
• Data wrangling (dplyr/tidyr)

Also refer to https://www.rstudio.com/resources/cheatsheets/ where many of the above are listed.